Transfer learning based hybrid model for power demand prediction of large-scale electric vehicles
Author
Abstract
Suggested Citation
DOI: 10.1016/j.energy.2024.131461
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Li, Jinwei & Ma, Rongjiang & Deng, Mengsi & Cao, Xiaoling & Wang, Xicheng & Wang, Xianlin, 2024. "A comparative study of clustering algorithms for intermittent heating demand considering time series," Applied Energy, Elsevier, vol. 353(PA).
- Yan, Qing-dong & Chen, Xiu-qi & Jian, Hong-chao & Wei, Wei & Wang, Wei-da & Wang, Heng, 2022. "Design of a deep inference framework for required power forecasting and predictive control on a hybrid electric mining truck," Energy, Elsevier, vol. 238(PC).
- Zhang, Xiaofeng & Kong, Xiaoying & Yan, Renshi & Liu, Yuting & Xia, Peng & Sun, Xiaoqin & Zeng, Rong & Li, Hongqiang, 2023. "Data-driven cooling, heating and electrical load prediction for building integrated with electric vehicles considering occupant travel behavior," Energy, Elsevier, vol. 264(C).
- Hao, Ying & Dong, Lei & Liang, Jun & Liao, Xiaozhong & Wang, Lijie & Shi, Lefeng, 2020. "Power forecasting-based coordination dispatch of PV power generation and electric vehicles charging in microgrid," Renewable Energy, Elsevier, vol. 155(C), pages 1191-1210.
- Lin, Xinyou & Xia, Yutian & Huang, Wei & Li, Hailin, 2021. "Trip distance adaptive power prediction control strategy optimization for a Plug-in Fuel Cell Electric Vehicle," Energy, Elsevier, vol. 224(C).
- Felipe Gonzalez & Marc Petit & Yannick Perez, 2021. "Plug-in behavior of electric vehicles users: Insights from a large-scale trial and impacts for grid integration studies," Post-Print hal-03363782, HAL.
- Fiori, Chiara & Ahn, Kyoungho & Rakha, Hesham A., 2016. "Power-based electric vehicle energy consumption model: Model development and validation," Applied Energy, Elsevier, vol. 168(C), pages 257-268.
- Tian, Zhirui & Liu, Weican & Jiang, Wenqian & Wu, Chenye, 2024. "CNNs-Transformer based day-ahead probabilistic load forecasting for weekends with limited data availability," Energy, Elsevier, vol. 293(C).
- Axsen, Jonn & Bailey, Joseph & Castro, Marisol Andrea, 2015. "Preference and lifestyle heterogeneity among potential plug-in electric vehicle buyers," Energy Economics, Elsevier, vol. 50(C), pages 190-201.
- Niu, Wente & Sun, Yuping & Zhang, Xiaowei & Lu, Jialiang & Liu, Hualin & Li, Qiaojing & Mu, Ying, 2023. "An ensemble transfer learning strategy for production prediction of shale gas wells," Energy, Elsevier, vol. 275(C).
- Fang, Xi & Gong, Guangcai & Li, Guannan & Chun, Liang & Li, Wenqiang & Peng, Pei, 2021. "A hybrid deep transfer learning strategy for short term cross-building energy prediction," Energy, Elsevier, vol. 215(PB).
- Zeng, Tao & Zhang, Caizhi & Hao, Dong & Cao, Dongpu & Chen, Jiawei & Chen, Jinrui & Li, Jin, 2020. "Data-driven approach for short-term power demand prediction of fuel cell hybrid vehicles," Energy, Elsevier, vol. 208(C).
- Ma, Tai-Yu & Faye, Sébastien, 2022. "Multistep electric vehicle charging station occupancy prediction using hybrid LSTM neural networks," Energy, Elsevier, vol. 244(PB).
- Sprei, Frances & Kempton, Willett, 2024. "Mental models guide electric vehicle charging," Energy, Elsevier, vol. 292(C).
- Wang, Shengyou & Zhuge, Chengxiang & Shao, Chunfu & Wang, Pinxi & Yang, Xiong & Wang, Shiqi, 2023. "Short-term electric vehicle charging demand prediction: A deep learning approach," Applied Energy, Elsevier, vol. 340(C).
- Yin, Wanjun & Ji, Jianbo, 2024. "Research on EV charging load forecasting and orderly charging scheduling based on model fusion," Energy, Elsevier, vol. 290(C).
- Yang, Lin & Cai, Yishan & Yang, Yixin & Deng, Zhongwei, 2020. "Supervisory long-term prediction of state of available power for lithium-ion batteries in electric vehicles," Applied Energy, Elsevier, vol. 257(C).
- Fei, Zicheng & Yang, Fangfang & Tsui, Kwok-Leung & Li, Lishuai & Zhang, Zijun, 2021. "Early prediction of battery lifetime via a machine learning based framework," Energy, Elsevier, vol. 225(C).
- Huber, Julian & Dann, David & Weinhardt, Christof, 2020. "Probabilistic forecasts of time and energy flexibility in battery electric vehicle charging," Applied Energy, Elsevier, vol. 262(C).
- Barman, Mayur & Dev Choudhury, N.B. & Sutradhar, Suman, 2018. "A regional hybrid GOA-SVM model based on similar day approach for short-term load forecasting in Assam, India," Energy, Elsevier, vol. 145(C), pages 710-720.
- Basso, Franco & Feijoo, Felipe & Pezoa, Raúl & Varas, Mauricio & Vidal, Brian, 2024. "The impact of electromobility in public transport: An estimation of energy consumption using disaggregated data in Santiago, Chile," Energy, Elsevier, vol. 286(C).
- Pan, Shaowei & Yang, Bo & Wang, Shukai & Guo, Zhi & Wang, Lin & Liu, Jinhua & Wu, Siyu, 2023. "Oil well production prediction based on CNN-LSTM model with self-attention mechanism," Energy, Elsevier, vol. 284(C).
- Huang, Wenxin & Wang, Jianguo & Wang, Jianping & Zeng, Haiyan & Zhou, Mi & Cao, Jinxin, 2024. "EV charging load profile identification and seasonal difference analysis via charging sessions data of charging stations," Energy, Elsevier, vol. 288(C).
- Yong, Jin Yi & Tan, Wen Shan & Khorasany, Mohsen & Razzaghi, Reza, 2023. "Electric vehicles destination charging: An overview of charging tariffs, business models and coordination strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Ren, Fei & Tian, Chenlu & Zhang, Guiqing & Li, Chengdong & Zhai, Yuan, 2022. "A hybrid method for power demand prediction of electric vehicles based on SARIMA and deep learning with integration of periodic features," Energy, Elsevier, vol. 250(C).
- Feng, Zhanyu & Zhang, Jian & Jiang, Han & Yao, Xuejian & Qian, Yu & Zhang, Haiyan, 2024. "Energy consumption prediction strategy for electric vehicle based on LSTM-transformer framework," Energy, Elsevier, vol. 302(C).
- Wang, Jun & Cao, Junxing, 2024. "Reservoir properties inversion using attention-based parallel hybrid network integrating feature selection and transfer learning," Energy, Elsevier, vol. 304(C).
- Li, Tao & Liu, Xiangyu & Li, Guannan & Wang, Xing & Ma, Jiangqiaoyu & Xu, Chengliang & Mao, Qianjun, 2024. "A systematic review and comprehensive analysis of building occupancy prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
- Kreft, Markus & Brudermueller, Tobias & Fleisch, Elgar & Staake, Thorsten, 2024. "Predictability of electric vehicle charging: Explaining extensive user behavior-specific heterogeneity," Applied Energy, Elsevier, vol. 370(C).
- Yao, Fang & He, Wenxuan & Wu, Youxi & Ding, Fei & Meng, Defang, 2022. "Remaining useful life prediction of lithium-ion batteries using a hybrid model," Energy, Elsevier, vol. 248(C).
- Kuang, Haoxuan & Qu, Haohao & Deng, Kunxiang & Li, Jun, 2024. "A physics-informed graph learning approach for citywide electric vehicle charging demand prediction and pricing," Applied Energy, Elsevier, vol. 363(C).
- Min, Haitao & Wu, Huiduo & Zhao, Honghui & Sun, Weiyi & Yu, Yuanbin, 2024. "Research on energy management strategy for fuel cell hybrid electric vehicles based on multi-scale information fusion," Applied Energy, Elsevier, vol. 368(C).
- Sheldon, Tamara L. & Dua, Rubal, 2018.
"Gasoline savings from clean vehicle adoption,"
Energy Policy, Elsevier, vol. 120(C), pages 418-424.
- Tamara Sheldon & Rubal Dua, 2018. "Gasoline Savings From Clean Vehicle Adoption," Discussion Papers ks-2018-dp026, King Abdullah Petroleum Studies and Research Center.
- Xie, Yunkun & Li, Yangyang & Zhao, Zhichao & Dong, Hao & Wang, Shuqian & Liu, Jingping & Guan, Jinhuan & Duan, Xiongbo, 2020. "Microsimulation of electric vehicle energy consumption and driving range," Applied Energy, Elsevier, vol. 267(C).
- Cheng, Fang & Liu, Hui, 2024. "Multi-step electric vehicles charging loads forecasting: An autoformer variant with feature extraction, frequency enhancement, and error correction blocks," Applied Energy, Elsevier, vol. 376(PB).
- Zhang, Chengquan & Kitamura, Hiroshi & Goto, Mika, 2024. "Feasibility of vehicle-to-grid (V2G) implementation in Japan: A regional analysis of the electricity supply and demand adjustment market," Energy, Elsevier, vol. 311(C).
- Yashraj Tripathy & Andrew McGordon & Anup Barai, 2020. "Improving Accessible Capacity Tracking at Low Ambient Temperatures for Range Estimation of Battery Electric Vehicles," Energies, MDPI, vol. 13(8), pages 1-18, April.
- K. S. Reddy & S. Aravindhan & Tapas K. Mallick, 2017. "Techno-Economic Investigation of Solar Powered Electric Auto-Rickshaw for a Sustainable Transport System," Energies, MDPI, vol. 10(6), pages 1, May.
- Stefano De Pinto & Pablo Camocardi & Christoforos Chatzikomis & Aldo Sorniotti & Francesco Bottiglione & Giacomo Mantriota & Pietro Perlo, 2020. "On the Comparison of 2- and 4-Wheel-Drive Electric Vehicle Layouts with Central Motors and Single- and 2-Speed Transmission Systems," Energies, MDPI, vol. 13(13), pages 1-24, June.
- Mukherjee, Arka & Carvalho, Margarida, 2021. "Dynamic decision making in a mixed market under cooperation: Towards sustainability," International Journal of Production Economics, Elsevier, vol. 241(C).
- Wang, Ying & Li, Hongmin & Jahanger, Atif & Li, Qiwei & Wang, Biao & Balsalobre-Lorente, Daniel, 2024. "A novel ensemble electricity load forecasting system based on a decomposition-selection-optimization strategy," Energy, Elsevier, vol. 312(C).
- Nan, Sirui & Tu, Ran & Li, Tiezhu & Sun, Jian & Chen, Haibo, 2022. "From driving behavior to energy consumption: A novel method to predict the energy consumption of electric bus," Energy, Elsevier, vol. 261(PA).
- Zhang, Ning & Li, Zhiying & Zou, Xun & Quiring, Steven M., 2019. "Comparison of three short-term load forecast models in Southern California," Energy, Elsevier, vol. 189(C).
- Kong, Xiangyu & Li, Chuang & Wang, Chengshan & Zhang, Yusen & Zhang, Jian, 2020. "Short-term electrical load forecasting based on error correction using dynamic mode decomposition," Applied Energy, Elsevier, vol. 261(C).
More about this item
Keywords
Deep learning; Large-scale electric vehicle; Power demand forecasting; Transfer learning;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:300:y:2024:i:c:s0360544224012349. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.